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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Degradation of Insulating Glass Units: Thermal Performance, Measurements and Energy Impacts

Insulating glass unit (IGU) degradation has been studied extensively. However, there is limited understanding of how present durability evaluation standards relate to product lifetime. Furthermore, there is debate on how to quantify performance of installed windows over time to better understand degradation processes. More knowledge on these topics is required to link durability evaluation to product lifetime projections based on energy performance. Energy models provide helpful estimations of total annual building energy consumption. However, most models are based on “as installed” performance of envelope components and fail to account for performance degradation. This can lead to an underestimation of building lifetime energy consumption. A better understanding of the relationship between durability and energy performance can inform integration of degradation dynamics into energy modeling software. This will improve lifetime building energy consumption estimations as well as inform appropriate retrofit strategies and timing. This paper reviews current durability literature, various standards for window performance ratings and weathering methods, existing in situ IGU energy performance measurement techniques, and whole-building energy effects. The challenges and disparities among various studies are analyzed and discussed. The authors hope that further work in this area will lead to the development of improved in situ test methods to assess IGU degradation in the field and link this knowledge to improved energy performance modeling approaches.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2013

On Multiscale Modeling: Preserving Energy Dissipation Across the Scales with Consistent Handshaking Methods

A mesh objective crack band model was implemented within the generalized method of cells micromechanics theory. This model was linked to a macroscale finite element model to predict post-peak strain softening in composite materials. Although a mesh objective theory was implemented at the microscale, it does not preclude pathological mesh dependence at the macroscale. To ensure mesh objectivity at both scales, the energy density and the energy release rate must be preserved identically across the two scales. This requires a consistent characteristic length or localization limiter. The effects of scaling (or not scaling) the dimensions of the microscale repeating unit cell (RUC), according to the macroscale element size, in a multiscale analysis was investigated using two examples. Additionally, the ramifications of the macroscale element shape, compared to the RUC, was studied.

Pineda, Evan J.↗
DOE OSTI2022

Magnesium- and intermetallic alloys-based hydrides for energy storage: modelling, synthesis and properties

Hydrides based on magnesium and intermetallic compounds provide a viable solution to the challenge of energy storage from renewable sources, thanks to their ability to absorb and desorb hydrogen in a reversible way with a proper tuning of pressure and temperature conditions. Therefore, they are expected to play an important role in the clean energy transition and in the deployment of hydrogen as an efficient energy vector. This review, by experts of Task 40 ‘Energy Storage and Conversion based on Hydrogen’ of the Hydrogen Technology Collaboration Programme of the International Energy Agency, reports on the latest activities of the working group ‘Magnesium- and Intermetallic alloys-based Hydrides for Energy Storage’. The following topics are covered by the review: multiscale modelling of hydrides and hydrogen sorption mechanisms; synthesis and processing techniques; catalysts for hydrogen sorption in Mg; Mg-based nanostructures and new compounds; hydrides based on intermetallic TiFe alloys, high entropy alloys, Laves phases, and Pd-containing alloys. Finally, an outlook is presented on current worldwide investments and future research directions for hydrogen-based energy storage.

Energy storage↗
DOE OSTI2020

Reserve Model of Energy Storage in Day-ahead Joint Energy and Reserve Markets: A Stochastic UC Solution

With many favorable advantages including fast response ability in particular, utility-level energy storage systems (ESS) are being integrated into energy and reserve markets to help mitigate uncertain renewable resources and fluctuant demands. This paper discusses a stochastic unit commitment (UC) model to explore capabilities of ESSs in providing valuable grid services by simultaneously joining energy and reserve markets. The proposed reserve model of ESSs presents the following features: (i) two constraints are proposed to formulate ESS’s reserve provision ability in each hour via six operation modes, namely increasing/reducing the level of charge, switching to discharge, increasing/reducing the level of discharge, switching to charge; (ii) as an energy-limited asset, constraints on ESS’s reserve deliverability across multiple hours is introduced to hold enough state of charge (SOC) headroom and floor room, guaranteeing that reserves cleared in individual hours are continuously deliverable over multiple successive hours without violating operation limits. Furthermore, a scenario-based UC model, which addresses uncertainties of renewables and demands, is adopted to evaluate reserves provided by ESSs and generators. To effectively solve the stochastic UC problem, the progressive hedging algorithm with heuristic approaches is discussed. A 6-bus system and a modified IEEE 118-bus system are used to illustrate effectiveness of the proposed approaches.

25 ENERGY STORAGE↗
DOE OSTI2026

AutoBEM: A scalable framework for nationwide building energy simulation and retrofit evaluation in the United States

This paper presents AutoBEM, an integrated, automated framework for nationwide building energy modeling and retrofit evaluation in the United States. Unlike prior UBEM platforms that either rely primarily on representative stock sampling or operate at city scale, AutoBEM automates the generation of building-resolved, physics-based EnergyPlus/OpenStudio simulation models at national scale using GIS-derived geometry, prototype-based assumptions, and standardized scalable workflows. Leveraging the Model America dataset and high-performance computing, AutoBEM generates and simulates energy models for 122.9 million buildings, representing 97.8% of the U.S. building stock. These models are being made publicly and freely available as the Model America v1.0 (MAv1) dataset. AutoBEM supports detailed, building-level assessments of energy consumption, CO2 emissions, and post-processed anthropogenic heat emissions (AHE), and evaluates 151 energy conservation measures (ECMs) using localized utility pricing and building characteristics. In addition, AutoBEM incorporates both typical and future climate conditions through integration with Typical Meteorological Year (TMY) and Future TMY (fTMY) weather data derived from IPCC scenarios. In a case study of Phoenix, Arizona, AutoBEM identified several high-efficiency HVAC upgrades and selected envelope measures with short modeled payback periods (1.5 years) for certain building types and standards. Simulations under future climate scenarios (SSP5–RCP8.5) project an 11.3% increase in electricity use and a 32% reduction in natural gas demand by 2100, underscoring the need for climate-adaptive retrofit planning. By enabling reproducible, bottom-up, and location-specific analysis at scale, AutoBEM provides a step toward a national digital twin of the built environment and supports data-driven screening and planning for decarbonization, resilience, and energy equity.

Li, Hang [ORNL] (ORCID:0000000306001920)↗
DOE OSTI2017

Nuclear Energy Advanced Modeling and Simulation (NEAMS) Accident Tolerant Fuels High Impact Problem: U 3 Si 2 Modeling Capabilities

U 3 Si 2 fuel is a potential candidate replacement for UO 2 in light water reactor fuel rods due to its higher uranium density and thermal conductivity. Its lower melting temperature and significant gaseous swelling may be of concern. The aggressive development schedule of the United States Department of Energy’s (DOE) Advanced Fuels Campaign (AFC) to have potential accident tolerant fuels (ATF) concepts in lead test rods or assemblies by 2022 has necessitated the need for advanced modeling and simulation techniques to investigate the behavior of these materials under normal operating and accident conditions. This report presents the modeling capabilities for U 3 Si 2 fuel at the engineering (continuum) scale developed as part of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) high impact problem (HIP). In this report, the models incorporated into the BISON fuel for U 3 Si 2 are described and comparisons to conventional UO 2 for separate effects cases are presented.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Enhancing Building Resilience: Maintaining Energy Efficiency and Thermal Comfort During Power Outages in Cold Climates

The increasing frequency and intensity of extreme weather events, such as heatwaves and cold snaps, present significant challenges to building energy performance and occupant comfort. Highly correlated with climate events are widespread long duration power interruptions that may affect thousands of buildings and millions of customers. This study evaluates the impact of building energy performance and occupant thermal comfort in medium-sized office buildings in a cold climate region. Using energy models representing pre-1980 and 2019 vintages, simulations were conducted to assess energy performance under typical weather conditions and occupant thermal comfort during power interrupted extreme cold snap and heatwave climate events under both current 2020s and future 2050s weather conditions. The results show a projected 33% increase in cooling energy demand and a 19% reduction in heating energy by 2050. Findings reveal that older buildings are more susceptible to cold discomfort during cold snaps, while modern airtight buildings are more vulnerable to overheating during heatwaves. Various passive energy efficiency measures, such as improved infiltration control, thermal windows, solar-controlled windows, and cool envelopes, were evaluated for their ability to mitigate thermal discomforts. Solar controlled windows and weatherstripping contribute to reducing cold thermal discomfort by 21% during a power-interrupted cold snap. Solar-controlled windows were found to reduce hot thermal discomfort by 34% during a future power-interrupted heatwave. The study highlights the importance of targeted retrofitting strategies to enhance thermal resilience, especially during power outages, to ensure occupant safety and comfort during extreme climate events.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2013

Nationwide water availability data for energy-water modeling

The purpose of this effort is to explore where the availability of water could be a limiting factor in the siting of new electric power generation. To support this analysis, water availability is mapped at the county level for the conterminous United States (3109 counties). Five water sources are individually considered, including unappropriated surface water, unappropriated groundwater, appropriated water (western U.S. only), municipal wastewater and brackish groundwater. Also mapped is projected growth in non-thermoelectric consumptive water demand to 2035. Finally, the water availability metrics are accompanied by estimated costs associated with utilizing that particular supply of water. Ultimately these data sets are being developed for use in the National Renewable Energy Laboratories' (NREL) Regional Energy Deployment System (ReEDS) model, designed to investigate the likely deployment of new energy installations in the U.S., subject to a number of constraints, particularly water.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1974

Energetic electrons in Jupiter's magnetosphere

A theoretical model for the energetic electron fluxes in the Jovian magnetosphere is developed. Electrons are transported inward from the solar wind or Jovian magnetospheric tail by radial diffusion. The radial diffusion is driven by fluctuating ionospheric dynamo electric fields associated with a neutral-wind tidal eigenmode at ionospheric altitudes. The tidal mode is excited by the electromagnetic coupling of the solar wind to the polar ionosphere. Two injection models are considered: (1) electron penetration through the dayside magnetopause - low-energy model; and (2) injection of electrons from an assumed magnetospheric tail - high-energy model. Both thermal solar-wind electrons and energetic solar-flare electrons are considered.

Coroniti, F. V.↗
DOE OSTI2013

An energy-limited model of algal biofuel production: Toward the next generation of advanced biofuels

Algal biofuels are increasingly important as a source of renewable energy. The absence of reliable thermodynamic and other property data, and the large amount of kinetic data that would normally be required have created a major barrier to simulation. Additionally, the absence of a generally accepted flowsheet for biofuel production means that detailed simulation of the wrong approach is a real possibility. This model of algal biofuel production estimates the necessary data and places it into a heuristic model using a commercial simulator that back-calculates the process structure required. Furthermore, complex kinetics can be obviated for now by putting the simulator into energy limitation and forcing it to solve for the missing design variables, such as bioreactor surface area, productivity, and oil content. The model does not attempt to prescribe a particular approach, but provides a guide towards a sound engineering approach to this challenging and important problem.

09 BIOMASS FUELS↗
DOE OSTI2022

Far-ultraviolet to FIR Spectral-energy Distribution Modeling of the Stellar Formation History of the M31 Bulge

M31 is being surveyed at far- and near-ultraviolet with the UVIT telescope on AstroSat. The central bulge of M31 was observed in the N279N (275–280 nm), N219M (200–240 nm), F172M (160–185 nm), F169M (145–175 nm), and F148W (120–180 nm) filters. These images are made publicly available here. The UVIT data are supplemented with Sloan Digital Sky Survey data in optical, Spitzer data in near-infrared and Herschel data in mid- and far-infrared. The resulting far-ultraviolet to IR spectral-energy distributions for the bulge and for 10 subregions, are modeled using combinations of simple stellar populations and with CIGALE models. We find a dominant old (10–12 Gyr) metal-rich ([Z/H] ~ 0.3) population and a younger (600 Myr) solar abundance ([Z/H] ~ 0) population throughout the bulge. For the innermost 120" we find an additional very young (25 Myr) metal-poor ([Z/H] ~ –0.7) population. The results are consistent with the most recent stellar population studies of the bulge, which find the two populations for the whole bulge and a third young population in the innermost bulge.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Development and Validation of a Latent Thermal Energy Storage Model Using Modelica

An abundance of research has been performed to understand the physics of latent thermal energy storage with phase change material. Some analytical and numerical findings have been validated by experiments, but there are few free and open-source models available to the general public for use in systems simulation and analysis. The Modelica programming language is a good avenue to make such models available, because it is object-oriented, equation-based, declarative, and acausal. These characteristics have enabling the creation of component model libraries that can be used to build larger system simulations for design analysis. The authors have previously developed a numerical framework to model phase change thermal storage and have validated model predictions with experiments. The objectives of this paper are to describe the transfer of the numerical framework to an implementation in a Modelica component model and to validate the Modelica model with data from the experiment and the original numerical framework.

25 ENERGY STORAGE↗
DOE OSTI2017

Nuclear Energy Advanced Modeling and Simulation (NEAMS) Accident Tolerant Fuels High Impact Problem: FeCrAl Modeling Capabilities

Iron-chromium-aluminum alloys are a potential candidate replacement for zirconium-based claddings in light water reactor fuel rods due to their increased strength (lower creep rates and higher yield stress) and slower oxidation kinetics with steam. Their larger neutron absorption cross-section necessitates thinner claddings and larger fuel pellets to maintain the same as-fabricated fuel-to-clad gap. The aggressive development schedule of the United States Department of Energy's (DOE) Advanced Fuels Campaign (AFC) to have potential accident tolerant fuels (ATF) concepts in lead test rods or assemblies by 2022 has necessitated the need for advanced modeling and simulation techniques to investigate the behavior of these materials under normal operating and accident conditions. This report presents the modeling capabilities for FeCrAl claddings at the engineering (continuum) scale developed as part of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) high impact problem (HIP). Sensitivity studies of select material parameters have been completed to determine their significance in predictions of important fuel performance parameters such as fuel centerline and surface temperatures, cladding stresses and strains, fission gas released, and rod internal pressure. Comparative analyses of FeCrAl and Zircaloy-4 claddings for separate effects conditions are presented.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

OpenStudio®-MCP [SWR-26-035]

OpenStudio®-MCP is a Model Context Protocol (MCP) server that lets AI assistants perform building energy modeling through natural language. Rather than requiring users to learn the OpenStudio® SDK, EnergyPlus® scripting, or Ruby/Python automation, the server translates conversational requests into sequences of tool calls that create models, design HVAC systems, run simulations, and extract results — all within a single chat session. The server's 124 tools are organized into a skills architecture where each skill encapsulates a domain of building energy modeling (envelope, HVAC, loads, weather, simulation, results) behind typed, LLM-friendly interfaces. High-leverage operations like applying ASHRAE 90.1 baseline systems or generating standards-compliant typical buildings are exposed as single tool calls that internally wire dozens of OpenStudio® objects. Bundled measures from ComStock™ and Openstudio® -common-measures-gem are wrapped with dedicated tools and typed arguments rather than exposed through a generic measure interface, so AI models get consistent, error-resistant recipes without needing to discover measure arguments at runtime. A key design decision is structured results extraction: six SQL-based tools return surgical ~300–1,000 token responses (end-use breakdowns, envelope summaries, HVAC sizing, timeseries data) instead of requiring the AI to parse ~100K-token raw HTML reports, making iterative design exploration practical within context window limits. The codebase is designed as a reference implementation — explicit, well-commented, and modular — so that other simulation engines (EnergyPlus® standalone, TRNSYS, DOE-2) can use it as a template for building their own MCP servers.

Ball, Brian [National Laboratory of the Rockies (N↗
DOE OSTI2022

Exploring New Ways to Classify Industries for Energy Analysis and Modeling

As the US moves closer to embracing a net zero greenhouse gas emissions position, combustion processes outside the power sector are becoming urgent concerns. Industry is an important end user of energy and relies on fossil fuels used directly for process heating and as feedstocks for a diverse range of applications. Fuel and energy use by industry is heterogeneous, meaning that even a single product group can vary broadly in its production routes and associated energy usage. In the US, the North American Industry Classification System (NAICS) serves as the basis for data collection and reporting. In turn, data based on NAICS is the foundation of most US energy modeling. Thus, the effectiveness of NAICS at representing energy use is a limiting condition for plans to improve energy efficiency and alternatives to fossil fuels in industry. Facility-level data to build more detail into heterogeneous sectors is scarce. This work explores alternative classification schemes for industry based on energy use characteristics, and provides a validation of an approach to make facility-level energy use estimates based on publicly available data from the greenhouse gas reporting program. First, several approaches to industrial taxonomies and their usefulness for industrial energy modeling are summarized. Data from Industrial Assessment Centers is analyzed using unsupervised machine learning techniques to detect clusters. Cladistics, an approach from biology, is adapted to energy and process characteristics of industries. A cladogram is presented for evolutionary directions in the iron and steel sector. Cladograms are a promising tool for constructing scenarios and summarizing directions of sectoral innovation. Finally, validation is performed for facility-level energy estimates from the US EPA Greenhouse Gas Reporting Program. This validation assists in making this data source available for use in energy modeling. Together, this work explores alternative approaches for categorizing industries in a way that aids understanding energy use, and presenting pathways for the future.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

X-Ray Energy Deposition Model for Simulating Asteroid Response to a Nuclear Planetary Defense Mitigation Mission

Abstract In the event of a potentially catastrophic asteroid impact, with sufficient warning time, deploying a nuclear device remains a powerful option for planetary defense if a kinetic impactor or other means of deflection proves insufficient. Predicting the effectiveness of a potential nuclear deflection or disruption mission depends on accurate multiphysics simulations of the device's X-ray energy deposition into the asteroid and the resulting material ablation. The relevant physics in these simulations span many orders of magnitude, require a variety of different complex physics packages, and are computationally expensive. Having an efficient and accurate way of modeling this system is necessary for exploring a mission's sensitivity to the asteroid's range of physical properties. To expedite future simulations, we present a completed X-ray energy deposition model developed using the radiation-hydrodynamics code Kull that can be used to initiate a nuclear mitigation mission calculation. The model spans a wide variety of possible mission initial conditions: four different asteroid-like materials at a range of porosities, two different source spectra, and a broad range of radiation fluences, source durations, and angles of incidence. Using blowoff momentum as the primary metric, the model-initiated simulation results match the full radiation-hydrodynamics results to within 10%.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1983

A thermomechanical model for energy propagation in a solid-fluid-solid system with one boundary in relative motion

A model is developed to predict the behavior of a thin fluid film in the wake of a tool in relative motion with respect to the table. Computational procedures are developed and limitations of the model are discussed. In general the fluid-interface temperature is controlled by conduction into the table. From the numerical results four regimes are identified: convective cooling, partial evaporation of the fluid film, extended evaporation due to a limiting evaporative heat flux, and surface dryout due to total evaporation of the fluid layer. These regimes are qualitatively illustrated in terms of the parameters film thickness, viscosity, and relative velocity.

Braun, M. J.↗